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german-traffic-sign-classification's Introduction

German Traffic Sign Classification

In this project, I used Python and TensorFlow to classify traffic signs.

Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. Download the dataset from here.

I was able to reach a +99% validation accuracy, and a 97.6% testing accuracy.

Pipeline architecture:

  • Load The Data.
  • Dataset Summary & Exploration
    • turning data into tensors
    • Getting images and their labels
    • turning images into tensors
  • Data Preprocessing.
    • Normalization
    • resize
  • Design a Model Architecture. -CNN Model
  • Model Training and Evaluation.
  • Testing the Model Using the Test Set.

Environement:

  • Python 3.7
  • TensorFlow 2.4.1 (GPU support)

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